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Use const generics. #1

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Nov 6, 2023
Merged

Use const generics. #1

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178bd56
Use const generics.
ahmedcharles Oct 12, 2023
27f9551
Remove redundant row/column count parameters
sunsided Nov 6, 2023
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31 changes: 15 additions & 16 deletions examples/gravity.rs
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Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,6 @@ use minikalman::{
create_buffer_temp_S_inv, create_buffer_temp_x, create_buffer_u, create_buffer_x,
create_buffer_y, create_buffer_z, matrix_data_t, Kalman, Measurement,
};
use stdint::uint_fast8_t;

/// Measurements.
///
Expand All @@ -39,12 +38,12 @@ const MEASUREMENT_ERROR: [matrix_data_t; 15] = [
-0.33747, 0.75873, 0.18135, -0.015764, 0.17869,
];

const NUM_STATES: usize = 3;
const NUM_INPUTS: usize = 0;
const NUM_MEASUREMENTS: usize = 1;

#[allow(non_snake_case)]
fn main() {
const NUM_STATES: uint_fast8_t = 3;
const NUM_INPUTS: uint_fast8_t = 0;
const NUM_MEASUREMENTS: uint_fast8_t = 1;

// System buffers.
let mut gravity_x = create_buffer_x!(NUM_STATES);
let mut gravity_A = create_buffer_A!(NUM_STATES);
Expand Down Expand Up @@ -74,9 +73,7 @@ fn main() {
let mut gravity_temp_PHt = create_buffer_temp_PHt!(NUM_STATES, NUM_MEASUREMENTS);
let mut gravity_temp_KHP = create_buffer_temp_KHP!(NUM_STATES);

let mut filter = Kalman::new_from_buffers(
NUM_STATES,
NUM_INPUTS,
let mut filter = Kalman::<NUM_STATES, NUM_INPUTS>::new_from_buffers(
&mut gravity_A,
&mut gravity_x,
&mut gravity_B,
Expand All @@ -88,9 +85,7 @@ fn main() {
&mut gravity_temp_BQ,
);

let mut measurement = Measurement::new_direct(
NUM_STATES,
NUM_MEASUREMENTS,
let mut measurement = Measurement::<NUM_STATES, NUM_MEASUREMENTS>::new_direct(
&mut gravity_H,
&mut gravity_z,
&mut gravity_R,
Expand Down Expand Up @@ -132,7 +127,7 @@ fn main() {
}

/// Initializes the state vector with initial assumptions.
fn initialize_state_vector(filter: &mut Kalman) {
fn initialize_state_vector(filter: &mut Kalman<'_, NUM_STATES, NUM_INPUTS>) {
filter.state_vector_apply(|state| {
state[0] = 0 as _; // position
state[1] = 0 as _; // velocity
Expand All @@ -148,7 +143,7 @@ fn initialize_state_vector(filter: &mut Kalman) {
/// v₁ = 1×v₀ + T×a₀
/// a₁ = 1×a₀
/// ```
fn initialize_state_transition_matrix(filter: &mut Kalman) {
fn initialize_state_transition_matrix(filter: &mut Kalman<'_, NUM_STATES, NUM_INPUTS>) {
filter.state_transition_apply(|a| {
// Time constant.
const T: matrix_data_t = 1 as _;
Expand All @@ -175,7 +170,7 @@ fn initialize_state_transition_matrix(filter: &mut Kalman) {
/// This defines how different states (linearly) influence each other
/// over time. In this setup we claim that position, velocity and acceleration
/// linearly are linearly independent.
fn initialize_state_covariance_matrix(filter: &mut Kalman) {
fn initialize_state_covariance_matrix(filter: &mut Kalman<'_, NUM_STATES, NUM_INPUTS>) {
filter.system_covariance_apply(|p| {
p.set(0, 0, 0.1 as _); // var(s)
p.set(0, 1, 0 as _); // cov(s, v)
Expand All @@ -195,7 +190,9 @@ fn initialize_state_covariance_matrix(filter: &mut Kalman) {
/// ```math
/// z = 1×s + 0×v + 0×a
/// ```
fn initialize_position_measurement_transformation_matrix(measurement: &mut Measurement) {
fn initialize_position_measurement_transformation_matrix(
measurement: &mut Measurement<'_, NUM_STATES, NUM_MEASUREMENTS>,
) {
measurement.measurement_transformation_apply(|h| {
h.set(0, 0, 1 as _); // z = 1*s
h.set(0, 1, 0 as _); // + 0*v
Expand All @@ -208,7 +205,9 @@ fn initialize_position_measurement_transformation_matrix(measurement: &mut Measu
/// This matrix describes the measurement covariances as well as the
/// individual variation components. It is the measurement counterpart
/// of the state covariance matrix.
fn initialize_position_measurement_process_noise_matrix(measurement: &mut Measurement) {
fn initialize_position_measurement_process_noise_matrix(
measurement: &mut Measurement<'_, NUM_STATES, NUM_MEASUREMENTS>,
) {
measurement.process_noise_apply(|r| {
r.set(0, 0, 0.5 as _); // var(s)
});
Expand Down
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